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In this task, you will be shown a conversation and a question. You should categorize the question into matching, summary, logic, arithmetic and, commonsense groups. Matching is a question entailed or paraphrased by exactly one sentence in a dialogue. The answer can be extracted from the same sentence. Questions that ca... | logic | task248_dream_classification | NIv2 | zs_opt | 0 | train |
Given the task definition and input, reply with output. In this task, you will be shown a conversation and a question. You should categorize the question into matching, summary, logic, arithmetic and, commonsense groups. Matching is a question entailed or paraphrased by exactly one sentence in a dialogue. The answer ca... | commonsense | task248_dream_classification | NIv2 | zs_opt | 5 | train |
In this task, you will be shown a conversation and a question. You should categorize the question into matching, summary, logic, arithmetic and, commonsense groups. Matching is a question entailed or paraphrased by exactly one sentence in a dialogue. The answer can be extracted from the same sentence. Questions that ca... | logic
| task248_dream_classification | NIv2 | fs_opt | 7 | train |
instruction:
In this task, you will be shown a conversation and a question. You should categorize the question into matching, summary, logic, arithmetic and, commonsense groups. Matching is a question entailed or paraphrased by exactly one sentence in a dialogue. The answer can be extracted from the same sentence. Ques... | logic
| task248_dream_classification | NIv2 | fs_opt | 9 | train |
Q: In this task, you will be shown a conversation and a question. You should categorize the question into matching, summary, logic, arithmetic and, commonsense groups. Matching is a question entailed or paraphrased by exactly one sentence in a dialogue. The answer can be extracted from the same sentence. Questions that... | matching | task248_dream_classification | NIv2 | zs_opt | 7 | train |
In this task, you will be shown a conversation and a question. You should categorize the question into matching, summary, logic, arithmetic and, commonsense groups. Matching is a question entailed or paraphrased by exactly one sentence in a dialogue. The answer can be extracted from the same sentence. Questions that ca... | logic | task248_dream_classification | NIv2 | zs_opt | 4 | train |
Teacher:In this task, you will be shown a conversation and a question. You should categorize the question into matching, summary, logic, arithmetic and, commonsense groups. Matching is a question entailed or paraphrased by exactly one sentence in a dialogue. The answer can be extracted from the same sentence. Questions... | commonsense | task248_dream_classification | NIv2 | zs_opt | 6 | train |
Given the task definition, example input & output, solve the new input case.
In this task, you will be shown a conversation and a question. You should categorize the question into matching, summary, logic, arithmetic and, commonsense groups. Matching is a question entailed or paraphrased by exactly one sentence in a di... | logic | task248_dream_classification | NIv2 | fs_opt | 1 | train |
In this task, you will be shown a conversation and a question. You should categorize the question into matching, summary, logic, arithmetic and, commonsense groups. Matching is a question entailed or paraphrased by exactly one sentence in a dialogue. The answer can be extracted from the same sentence. Questions that ca... | logic | task248_dream_classification | NIv2 | zs_opt | 4 | test |
In this task, you will be shown a conversation and a question. You should categorize the question into matching, summary, logic, arithmetic and, commonsense groups. Matching is a question entailed or paraphrased by exactly one sentence in a dialogue. The answer can be extracted from the same sentence. Questions that ca... | logic | task248_dream_classification | NIv2 | zs_opt | 4 | validation |
Instructions: You will be given a context and a verb separated with a newline character. You have to identify if the given verb implies an opinion, an intention, a wish or not. Please note that a verb refers to an intention only if it refers to an event planned to happen in the future and is not conditional (or part of... | No | task456_matres_intention_classification | NIv2 | zs_opt | 3 | train |
Instructions: You will be given a context and a verb separated with a newline character. You have to identify if the given verb implies an opinion, an intention, a wish or not. Please note that a verb refers to an intention only if it refers to an event planned to happen in the future and is not conditional (or part of... | No | task456_matres_intention_classification | NIv2 | zs_opt | 3 | train |
You will be given a context and a verb separated with a newline character. You have to identify if the given verb implies an opinion, an intention, a wish or not. Please note that a verb refers to an intention only if it refers to an event planned to happen in the future and is not conditional (or part of a condition).... | Yes | task456_matres_intention_classification | NIv2 | fs_opt | 6 | train |
Definition: You will be given a context and a verb separated with a newline character. You have to identify if the given verb implies an opinion, an intention, a wish or not. Please note that a verb refers to an intention only if it refers to an event planned to happen in the future and is not conditional (or part of a... | No | task456_matres_intention_classification | NIv2 | zs_opt | 2 | train |
Instructions: You will be given a context and a verb separated with a newline character. You have to identify if the given verb implies an opinion, an intention, a wish or not. Please note that a verb refers to an intention only if it refers to an event planned to happen in the future and is not conditional (or part of... | No | task456_matres_intention_classification | NIv2 | zs_opt | 3 | train |
You will be given a context and a verb separated with a newline character. You have to identify if the given verb implies an opinion, an intention, a wish or not. Please note that a verb refers to an intention only if it refers to an event planned to happen in the future and is not conditional (or part of a condition).... | Yes | task456_matres_intention_classification | NIv2 | zs_opt | 0 | train |
You will be given a context and a verb separated with a newline character. You have to identify if the given verb implies an opinion, an intention, a wish or not. Please note that a verb refers to an intention only if it refers to an event planned to happen in the future and is not conditional (or part of a condition).... | No | task456_matres_intention_classification | NIv2 | zs_opt | 0 | train |
Q: You will be given a context and a verb separated with a newline character. You have to identify if the given verb implies an opinion, an intention, a wish or not. Please note that a verb refers to an intention only if it refers to an event planned to happen in the future and is not conditional (or part of a conditio... | Yes | task456_matres_intention_classification | NIv2 | zs_opt | 7 | train |
You will be given a context and a verb separated with a newline character. You have to identify if the given verb implies an opinion, an intention, a wish or not. Please note that a verb refers to an intention only if it refers to an event planned to happen in the future and is not conditional (or part of a condition).... | No | task456_matres_intention_classification | NIv2 | zs_opt | 0 | test |
You will be given a context and a verb separated with a newline character. You have to identify if the given verb implies an opinion, an intention, a wish or not. Please note that a verb refers to an intention only if it refers to an event planned to happen in the future and is not conditional (or part of a condition).... | Solution: No | task456_matres_intention_classification | NIv2 | fs_opt | 5 | validation |
In this task, you are given a hateful post in Bengali that expresses hate or encourages violence towards a person or a group based on the protected characteristics such as race, religion, sex, and sexual orientation. You are expected to classify the post into two classes: personal or non-personal depending on the topic... | non-personal | task1490_bengali_personal_hate_speech_binary_classification | NIv2 | fs_opt | 6 | train |
Detailed Instructions: In this task, you are given a hateful post in Bengali that expresses hate or encourages violence towards a person or a group based on the protected characteristics such as race, religion, sex, and sexual orientation. You are expected to classify the post into two classes: personal or non-personal... | non-personal | task1490_bengali_personal_hate_speech_binary_classification | NIv2 | zs_opt | 9 | train |
You will be given a definition of a task first, then some input of the task.
In this task, you are given a hateful post in Bengali that expresses hate or encourages violence towards a person or a group based on the protected characteristics such as race, religion, sex, and sexual orientation. You are expected to classi... | personal | task1490_bengali_personal_hate_speech_binary_classification | NIv2 | zs_opt | 1 | train |
In this task, you are given a hateful post in Bengali that expresses hate or encourages violence towards a person or a group based on the protected characteristics such as race, religion, sex, and sexual orientation. You are expected to classify the post into two classes: personal or non-personal depending on the topic... | personal
| task1490_bengali_personal_hate_speech_binary_classification | NIv2 | fs_opt | 1 | train |
In this task, you are given a hateful post in Bengali that expresses hate or encourages violence towards a person or a group based on the protected characteristics such as race, religion, sex, and sexual orientation. You are expected to classify the post into two classes: personal or non-personal depending on the topic... | non-personal
| task1490_bengali_personal_hate_speech_binary_classification | NIv2 | fs_opt | 0 | train |
In this task, you are given a hateful post in Bengali that expresses hate or encourages violence towards a person or a group based on the protected characteristics such as race, religion, sex, and sexual orientation. You are expected to classify the post into two classes: personal or non-personal depending on the topic... | personal
| task1490_bengali_personal_hate_speech_binary_classification | NIv2 | fs_opt | 6 | train |
In this task, you are given a hateful post in Bengali that expresses hate or encourages violence towards a person or a group based on the protected characteristics such as race, religion, sex, and sexual orientation. You are expected to classify the post into two classes: personal or non-personal depending on the topic... | non-personal | task1490_bengali_personal_hate_speech_binary_classification | NIv2 | fs_opt | 6 | train |
Given the task definition and input, reply with output. In this task, you are given a hateful post in Bengali that expresses hate or encourages violence towards a person or a group based on the protected characteristics such as race, religion, sex, and sexual orientation. You are expected to classify the post into two ... | non-personal | task1490_bengali_personal_hate_speech_binary_classification | NIv2 | zs_opt | 5 | train |
Detailed Instructions: In this task, you are given a hateful post in Bengali that expresses hate or encourages violence towards a person or a group based on the protected characteristics such as race, religion, sex, and sexual orientation. You are expected to classify the post into two classes: personal or non-personal... | non-personal | task1490_bengali_personal_hate_speech_binary_classification | NIv2 | fs_opt | 4 | test |
In this task, you are given a hateful post in Bengali that expresses hate or encourages violence towards a person or a group based on the protected characteristics such as race, religion, sex, and sexual orientation. You are expected to classify the post into two classes: personal or non-personal depending on the topic... | Solution: personal | task1490_bengali_personal_hate_speech_binary_classification | NIv2 | fs_opt | 5 | validation |
Given a question, generate a paraphrase of that question wihout changing the meaning of it. Your answer should reword the given sentence, but not add information to it or remove information from it. The answer to your question should be the same as the answer to the original question.
--------
Question: Question: the c... | which president of the us has more than one vice president?
| task442_com_qa_paraphrase_question_generation | NIv2 | fs_opt | 7 | train |
Given the task definition, example input & output, solve the new input case.
Given a question, generate a paraphrase of that question wihout changing the meaning of it. Your answer should reword the given sentence, but not add information to it or remove information from it. The answer to your question should be the sa... | what was the fathers name of mahatma gandhi? | task442_com_qa_paraphrase_question_generation | NIv2 | fs_opt | 1 | train |
Given a question, generate a paraphrase of that question wihout changing the meaning of it. Your answer should reword the given sentence, but not add information to it or remove information from it. The answer to your question should be the same as the answer to the original question.
Q: Question: where was jackie robi... | what place was jackie robinson born? | task442_com_qa_paraphrase_question_generation | NIv2 | zs_opt | 4 | train |
Definition: Given a question, generate a paraphrase of that question wihout changing the meaning of it. Your answer should reword the given sentence, but not add information to it or remove information from it. The answer to your question should be the same as the answer to the original question.
Input: Question: what ... | what nba team has the most hall of famers? | task442_com_qa_paraphrase_question_generation | NIv2 | zs_opt | 2 | train |
Q: Given a question, generate a paraphrase of that question wihout changing the meaning of it. Your answer should reword the given sentence, but not add information to it or remove information from it. The answer to your question should be the same as the answer to the original question.
Question: who was prophet muham... | who was the first wife of prophet mohammed? | task442_com_qa_paraphrase_question_generation | NIv2 | zs_opt | 7 | train |
Given a question, generate a paraphrase of that question wihout changing the meaning of it. Your answer should reword the given sentence, but not add information to it or remove information from it. The answer to your question should be the same as the answer to the original question.
One example is below.
Q: Question:... | samuel eto'o is from where? | task442_com_qa_paraphrase_question_generation | NIv2 | fs_opt | 9 | train |
Given a question, generate a paraphrase of that question wihout changing the meaning of it. Your answer should reword the given sentence, but not add information to it or remove information from it. The answer to your question should be the same as the answer to the original question.
Q: Question: kenya borders the oce... | what ocean borders keyna to the southeast? | task442_com_qa_paraphrase_question_generation | NIv2 | zs_opt | 4 | train |
Teacher: Given a question, generate a paraphrase of that question wihout changing the meaning of it. Your answer should reword the given sentence, but not add information to it or remove information from it. The answer to your question should be the same as the answer to the original question.
Teacher: Now, understand ... | which tv show did leonardo dicaprio participle in? | task442_com_qa_paraphrase_question_generation | NIv2 | fs_opt | 2 | train |
Given the task definition and input, reply with output. Given a question, generate a paraphrase of that question wihout changing the meaning of it. Your answer should reword the given sentence, but not add information to it or remove information from it. The answer to your question should be the same as the answer to t... | in which city was alfred wegener born and who raised him? | task442_com_qa_paraphrase_question_generation | NIv2 | zs_opt | 5 | test |
You will be given a definition of a task first, then some input of the task.
Given a question, generate a paraphrase of that question wihout changing the meaning of it. Your answer should reword the given sentence, but not add information to it or remove information from it. The answer to your question should be the sa... | what is the population of nevada carson city? | task442_com_qa_paraphrase_question_generation | NIv2 | zs_opt | 1 | validation |
You are given a statement in Croatian, a question word and four choices in Croation. If the question word is "cause", you should choose the option that is most likely to be the cause of the statement. If the question word is "effect", you should pick the choice that is most likely to be a consequence of the statement. ... | Našao sam posao s boljom plaćom. | task1628_copa_hr_question_answering | NIv2 | fs_opt | 6 | train |
Definition: You are given a statement in Croatian, a question word and four choices in Croation. If the question word is "cause", you should choose the option that is most likely to be the cause of the statement. If the question word is "effect", you should pick the choice that is most likely to be a consequence of the... | Bio je iznenađen. | task1628_copa_hr_question_answering | NIv2 | zs_opt | 2 | train |
You are given a statement in Croatian, a question word and four choices in Croation. If the question word is "cause", you should choose the option that is most likely to be the cause of the statement. If the question word is "effect", you should pick the choice that is most likely to be a consequence of the statement. ... | Korisnik je pomaknuo miš. | task1628_copa_hr_question_answering | NIv2 | fs_opt | 9 | train |
Detailed Instructions: You are given a statement in Croatian, a question word and four choices in Croation. If the question word is "cause", you should choose the option that is most likely to be the cause of the statement. If the question word is "effect", you should pick the choice that is most likely to be a consequ... | Otmičar je prijetio da će ozlijediti taoca. | task1628_copa_hr_question_answering | NIv2 | zs_opt | 9 | train |
You are given a statement in Croatian, a question word and four choices in Croation. If the question word is "cause", you should choose the option that is most likely to be the cause of the statement. If the question word is "effect", you should pick the choice that is most likely to be a consequence of the statement. ... | Zbunio se. | task1628_copa_hr_question_answering | NIv2 | fs_opt | 8 | train |
You are given a statement in Croatian, a question word and four choices in Croation. If the question word is "cause", you should choose the option that is most likely to be the cause of the statement. If the question word is "effect", you should pick the choice that is most likely to be a consequence of the statement. ... | Mnogi su građani pronašli utočište na drugim područjima.
| task1628_copa_hr_question_answering | NIv2 | fs_opt | 0 | train |
You will be given a definition of a task first, then some input of the task.
You are given a statement in Croatian, a question word and four choices in Croation. If the question word is "cause", you should choose the option that is most likely to be the cause of the statement. If the question word is "effect", you shou... | Rezao je luk. | task1628_copa_hr_question_answering | NIv2 | zs_opt | 1 | train |
Part 1. Definition
You are given a statement in Croatian, a question word and four choices in Croation. If the question word is "cause", you should choose the option that is most likely to be the cause of the statement. If the question word is "effect", you should pick the choice that is most likely to be a consequence... | Osjetio je miris njezina parfema. | task1628_copa_hr_question_answering | NIv2 | fs_opt | 7 | train |
Q: You are given a statement in Croatian, a question word and four choices in Croation. If the question word is "cause", you should choose the option that is most likely to be the cause of the statement. If the question word is "effect", you should pick the choice that is most likely to be a consequence of the statemen... | Vlasnik je prekorio psića. | task1628_copa_hr_question_answering | NIv2 | zs_opt | 7 | test |
You are given a statement in Croatian, a question word and four choices in Croation. If the question word is "cause", you should choose the option that is most likely to be the cause of the statement. If the question word is "effect", you should pick the choice that is most likely to be a consequence of the statement. ... | Njihovo je stanište uništeno. | task1628_copa_hr_question_answering | NIv2 | zs_opt | 0 | validation |
A text is given in Marathi. Translate it from the Marathi language to the Oriya language. The translation must not omit or add information to the original sentence.
Ex Input:
त्यावेळी आम्ही जापानबरोबर नौवहन क्षेत्रासंदर्भात एक महत्वपूर्ण करार केला.
Ex Output:
ତାଙ୍କୁ ମୋଦୀ ଉପରେ ରାଗ ଆସିବ କି ଆସିବ ନାହିଁ?
Ex Input:
अन्न ... | ନେହରୁଜୀ ଆମକୁ ଶିଖାଇଥିଲେ ଯେ ଭାରତର ଶତାଧିକ ବର୍ଷର ଐତିହ୍ୟ ଏବଂ ପରମ୍ପରା, ଯାହାକୁ ନେଇ ଆଜି ବି ଆମେ ଗର୍ବିତ, ତାହାର ଟେକ୍ନୋଲଜି ସହିତ ତାଳମେଳ ସମ୍ଭବ ଅଟେ, ଏବଂ ଏହି ପରମ୍ପରା ଆଧୁନିକ ସମାଜର ନିର୍ମାଣ ପ୍ରୟାସରେ ସହାୟକ ହୋଇପାରିବ ।
| task1055_pib_translation_marathi_oriya | NIv2 | fs_opt | 1 | train |
You will be given a definition of a task first, then some input of the task.
A text is given in Marathi. Translate it from the Marathi language to the Oriya language. The translation must not omit or add information to the original sentence.
मला नाही वाटत की, माझ्या देशातला एकही युवक आता भ्रष्टाचार सहन करेल.
Output: | ଦ ଫ୍ୟାକ୍ଟୋରିଜ୍ (ସଂଶୋଧନ) ବିଲ୍, 2014 | task1055_pib_translation_marathi_oriya | NIv2 | zs_opt | 1 | train |
A text is given in Marathi. Translate it from the Marathi language to the Oriya language. The translation must not omit or add information to the original sentence.
[EX Q]: आज आपल्या देशात जवळ जवळ ४५० विमाने वापरात आहेत. देशात विमान सेवा देत आहेत, सरकारी असोत वा खाजगी, सर्व मिळून.
[EX A]: ବୋଧ ହୁଏ ଏହା ପୂର୍ବରୁ 20 ବର୍ଷ, ... | କେହି ପର୍ଯ୍ୟଟକ ଆମକୁ ପଚାରିବ ଯେ ଆପଣ ହିନ୍ଦୁସ୍ତାନରୁ ଆସୁଛନ୍ତି, ଆପଣ ତାମିଲନାଡ଼ୁର ସେହି ମନ୍ଦିର ଦେଖିଛନ୍ତି?
| task1055_pib_translation_marathi_oriya | NIv2 | fs_opt | 6 | train |
Teacher: A text is given in Marathi. Translate it from the Marathi language to the Oriya language. The translation must not omit or add information to the original sentence.
Teacher: Now, understand the problem? If you are still confused, see the following example:
मी जेथे जात असे तेथे सांडणीच्या दुधाच्या विषयावरून माझ... | ଏହାତ ପାଳନ କରାଯାଏ, କିନ୍ତୁ ଭାରତରେ 80 ବର୍ଷର ଏକ ବିଶେଷ ମହତ୍ୱ ରହିଛି । ଆଉ ଯେତେବେଳେ କୌଣସି ଲୋକର ଜୀବନରେ 80 ବର୍ଷ ହୋଇଥାଏ, ଅର୍ଥାତ ସହସ୍ର ଚନ୍ଦ୍ର-ଦର୍ଶନର ପର୍ବ ହୋଇଥାଏ । 80 ବର୍ଷର ଯାତ୍ରାରେ ବ୍ୟକ୍ତି ଅଥବା ସଂସ୍ଥା ଏକ ହଜାର ଥର ପୂର୍ଣ୍ଣ ଚନ୍ଦ୍ର ଦର୍ଶନ କରିଥାଏ । | task1055_pib_translation_marathi_oriya | NIv2 | fs_opt | 2 | train |
A text is given in Marathi. Translate it from the Marathi language to the Oriya language. The translation must not omit or add information to the original sentence.
[EX Q]: तुम्हाला आठवत असेल, पूर्वी पीआयओ आणि ओसीआय या दोन वेगवेगळ्या योजना होत्या. अनेक लोकांना या दोन योजनांमधला फरकही कळत नसे.
[EX A]: ଏହି ଅବସରରେ କେନ୍ଦ୍... | ଆସନ୍ତା ବର୍ଷ ସୁଦ୍ଧା ମୋଟ 8 କୋଟି ସଂଯୋଗ ଲକ୍ଷ୍ୟ
| task1055_pib_translation_marathi_oriya | NIv2 | fs_opt | 6 | train |
You will be given a definition of a task first, then some input of the task.
A text is given in Marathi. Translate it from the Marathi language to the Oriya language. The translation must not omit or add information to the original sentence.
इथल्या विकास यात्रेचे भागीदार बनले आहेत.
Output: | ମାହାମାନ୍ୟ ଡଃ ଉଜ୍ଜିଏଲ ନାଗିଜିମାନା, ଅର୍ଥ ଓ ଆର୍ଥିକ ଯୋଜନା ମନ୍ତ୍ରୀ | task1055_pib_translation_marathi_oriya | NIv2 | zs_opt | 1 | train |
Teacher: A text is given in Marathi. Translate it from the Marathi language to the Oriya language. The translation must not omit or add information to the original sentence.
Teacher: Now, understand the problem? If you are still confused, see the following example:
मी जेथे जात असे तेथे सांडणीच्या दुधाच्या विषयावरून माझ... | ପ୍ରଖ୍ୟାତ ତେଲୁଗୁ କବି, ଗୀତିକାର ଏବଂ ଲେଖକ ସି. | task1055_pib_translation_marathi_oriya | NIv2 | fs_opt | 2 | train |
Teacher:A text is given in Marathi. Translate it from the Marathi language to the Oriya language. The translation must not omit or add information to the original sentence.
Teacher: Now, understand the problem? Solve this instance: आपण सर्व मिळून एक असा भारत घडवूया जिथे,शेतकऱ्याला विवंचना नसतील, तो सुखाची झोप घेऊ शकेल.... | ଆମେ ସବୁ ମିଳମିଶି ଏଭଳି ଏକ ଭାରତ ନିର୍ମାଣ କରିବା, ଯେଉଁଠାରେ ଭ୍ରଷ୍ଟାଚାର ଏବଂ ପରିବାର-ବଂଶବାଦ ସହିତ କୌଣସି ସାଲିସ ହେଉ ନ ଥିବ । | task1055_pib_translation_marathi_oriya | NIv2 | zs_opt | 6 | train |
A text is given in Marathi. Translate it from the Marathi language to the Oriya language. The translation must not omit or add information to the original sentence.
बदलत्या तंत्रज्ञानाच्या माध्यमातून . आणि माध्यमेसुद्धा बदलली आहेत, ती भलेही बदलली असली तरी आमचा हेतू तोच आहे. | 2- ପ୍ରଥମ ଥର ପାଇଁ, ସମସ୍ତ ଶିକ୍ଷକ ସିଧାସଳଖ ଭାବେ ଏଥିପାଇଁ ଆବେଦନ କରିପାରିବେ ଏବଂ ପୁରସ୍କାର ପାଇଁ ମନୋନୟନ କରିପାରିବେ (ଏହି ସୁବିଧା ପୂର୍ବରୁ ଥିବା ନିୟମାବଳୀରେ ନଥିଲା) | task1055_pib_translation_marathi_oriya | NIv2 | zs_opt | 0 | test |
Teacher: A text is given in Marathi. Translate it from the Marathi language to the Oriya language. The translation must not omit or add information to the original sentence.
Teacher: Now, understand the problem? If you are still confused, see the following example:
मी जेथे जात असे तेथे सांडणीच्या दुधाच्या विषयावरून माझ... | ଆତଙ୍କବାଦ ଏବଂ ଅତିବାଦର ଲାଳନପାଳନ କରୁଥିବା ଶକ୍ତିଗୁଡ଼ିକୁ ଦୂରରେ ରଖିବା ପାଇଁ | task1055_pib_translation_marathi_oriya | NIv2 | fs_opt | 2 | validation |
Given the task definition and input, reply with output. In this task, you have to generate the title of the recipe given its required ingredients and directions.
ingredients: '3 12 lbs stew meat, cut into 2-inch pieces', '2 (15 ounce) cans tomato sauce', '14 cup chili powder', '2 cups beef base (more may be needed de... | Chili Colorado | task569_recipe_nlg_text_generation | NIv2 | zs_opt | 5 | train |
Given the task definition, example input & output, solve the new input case.
In this task, you have to generate the title of the recipe given its required ingredients and directions.
Example: ingredients: '1 cup minced onion', '1 1/2 tablespoons lemon juice', '3/4 teaspoon Hungarian paprika', '3/4 teaspoon ground cayen... | Marinated Three-Bean Salad | task569_recipe_nlg_text_generation | NIv2 | fs_opt | 1 | train |
Detailed Instructions: In this task, you have to generate the title of the recipe given its required ingredients and directions.
See one example below:
Problem: ingredients: '1 cup minced onion', '1 1/2 tablespoons lemon juice', '3/4 teaspoon Hungarian paprika', '3/4 teaspoon ground cayenne pepper', '1/4 teaspoon salt'... | Chinese Fried Rice | task569_recipe_nlg_text_generation | NIv2 | fs_opt | 4 | train |
In this task, you have to generate the title of the recipe given its required ingredients and directions.
Input: Consider Input: ingredients: '2 to 8 boned chicken breasts', '6 to 8 slices bacon', '1 pkg. chipped beef', '8 oz. sour cream', '1 can cream of mushroom soup',<sep> directions: 'Grease a baking dish.', 'Cov... | Output: Thai-Style Shrimp And Veggies With Toasted Coconut Rice
| task569_recipe_nlg_text_generation | NIv2 | fs_opt | 2 | train |
Given the task definition, example input & output, solve the new input case.
In this task, you have to generate the title of the recipe given its required ingredients and directions.
Example: ingredients: '1 cup minced onion', '1 1/2 tablespoons lemon juice', '3/4 teaspoon Hungarian paprika', '3/4 teaspoon ground cayen... | Amaranth Breakfast Cereal with Blueberries | task569_recipe_nlg_text_generation | NIv2 | fs_opt | 1 | train |
Detailed Instructions: In this task, you have to generate the title of the recipe given its required ingredients and directions.
See one example below:
Problem: ingredients: '1 cup minced onion', '1 1/2 tablespoons lemon juice', '3/4 teaspoon Hungarian paprika', '3/4 teaspoon ground cayenne pepper', '1/4 teaspoon salt'... | Simple Hand-Kneaded Bread (proved in the fridge) | task569_recipe_nlg_text_generation | NIv2 | fs_opt | 4 | train |
In this task, you have to generate the title of the recipe given its required ingredients and directions.
Let me give you an example: ingredients: '1 cup minced onion', '1 1/2 tablespoons lemon juice', '3/4 teaspoon Hungarian paprika', '3/4 teaspoon ground cayenne pepper', '1/4 teaspoon salt', <sep> directions: 'Rinse... | Becka'S Macaroni & Cheese | task569_recipe_nlg_text_generation | NIv2 | fs_opt | 8 | train |
In this task, you have to generate the title of the recipe given its required ingredients and directions.
Example input: ingredients: '1 cup minced onion', '1 1/2 tablespoons lemon juice', '3/4 teaspoon Hungarian paprika', '3/4 teaspoon ground cayenne pepper', '1/4 teaspoon salt', <sep> directions: 'Rinse onions in si... | Bacon Basil Shrimp on a Stick | task569_recipe_nlg_text_generation | NIv2 | fs_opt | 3 | train |
Q: In this task, you have to generate the title of the recipe given its required ingredients and directions.
ingredients: '4 boneless skinless chicken breast halves (about 1-1/4 lb.), cut into strips', '1 cup prepared GOOD SEASONS Roasted Garlic Salad Dressing & Recipe Mix, divided', '1 lb. pasta, uncooked', '3 cups b... | Chicken & Pasta Toss with Sun Dried Tomatoes | task569_recipe_nlg_text_generation | NIv2 | zs_opt | 7 | test |
Given the task definition and input, reply with output. In this task, you have to generate the title of the recipe given its required ingredients and directions.
ingredients: '1 1/4 c. all-purpose or unbleached flour', '1/2 c. powdered sugar', '1/2 c. margarine or butter',<sep> directions: 'Using pastry blender or fo... | Krispy Chocolate Caramel Bars | task569_recipe_nlg_text_generation | NIv2 | zs_opt | 5 | validation |
Given the task definition, example input & output, solve the new input case.
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a ba... | good | task1575_amazon_reviews_multi_sentiment_classification | NIv2 | fs_opt | 1 | train |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Example Input: 书里说有... | bad
| task1575_amazon_reviews_multi_sentiment_classification | NIv2 | fs_opt | 3 | train |
You will be given a definition of a task first, then some input of the task.
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a ba... | bad | task1575_amazon_reviews_multi_sentiment_classification | NIv2 | zs_opt | 1 | train |
Definition: In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Input: S... | bad | task1575_amazon_reviews_multi_sentiment_classification | NIv2 | zs_opt | 2 | train |
Part 1. Definition
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
P... | bad | task1575_amazon_reviews_multi_sentiment_classification | NIv2 | fs_opt | 7 | train |
Instructions: In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Input:... | good | task1575_amazon_reviews_multi_sentiment_classification | NIv2 | zs_opt | 3 | train |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Example: The bags ca... | Solution: bad | task1575_amazon_reviews_multi_sentiment_classification | NIv2 | fs_opt | 5 | train |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Let me give you an ... | bad | task1575_amazon_reviews_multi_sentiment_classification | NIv2 | fs_opt | 8 | train |
Detailed Instructions: In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good review... | good | task1575_amazon_reviews_multi_sentiment_classification | NIv2 | zs_opt | 8 | test |
Part 1. Definition
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
P... | good | task1575_amazon_reviews_multi_sentiment_classification | NIv2 | fs_opt | 7 | validation |
Teacher:Given a premise and two alternatives, choose the alternative that is a more plausible cause or effect of the situation described by the premise. The input format is "premise
(1)alternative_1(2)alternative_2", the output should either be "1" or "2" based on your judgment.
Teacher: Now, understand the problem? So... | 1 | task827_copa_commonsense_reasoning | NIv2 | zs_opt | 6 | train |
Given a premise and two alternatives, choose the alternative that is a more plausible cause or effect of the situation described by the premise. The input format is "premise
(1)alternative_1(2)alternative_2", the output should either be "1" or "2" based on your judgment.
One example is below.
Q: The women met for coffe... | 2 | task827_copa_commonsense_reasoning | NIv2 | fs_opt | 9 | train |
Given a premise and two alternatives, choose the alternative that is a more plausible cause or effect of the situation described by the premise. The input format is "premise
(1)alternative_1(2)alternative_2", the output should either be "1" or "2" based on your judgment.
Example: The women met for coffee.
(1)The cafe r... | Solution: 1 | task827_copa_commonsense_reasoning | NIv2 | fs_opt | 5 | train |
You will be given a definition of a task first, then some input of the task.
Given a premise and two alternatives, choose the alternative that is a more plausible cause or effect of the situation described by the premise. The input format is "premise
(1)alternative_1(2)alternative_2", the output should either be "1" or... | 2 | task827_copa_commonsense_reasoning | NIv2 | zs_opt | 1 | train |
You will be given a definition of a task first, then some input of the task.
Given a premise and two alternatives, choose the alternative that is a more plausible cause or effect of the situation described by the premise. The input format is "premise
(1)alternative_1(2)alternative_2", the output should either be "1" or... | 1 | task827_copa_commonsense_reasoning | NIv2 | zs_opt | 1 | train |
Definition: Given a premise and two alternatives, choose the alternative that is a more plausible cause or effect of the situation described by the premise. The input format is "premise
(1)alternative_1(2)alternative_2", the output should either be "1" or "2" based on your judgment.
Input: I learned how to play the boa... | 1 | task827_copa_commonsense_reasoning | NIv2 | zs_opt | 2 | train |
Given a premise and two alternatives, choose the alternative that is a more plausible cause or effect of the situation described by the premise. The input format is "premise
(1)alternative_1(2)alternative_2", the output should either be "1" or "2" based on your judgment.
One example is below.
Q: The women met for coffe... | 2 | task827_copa_commonsense_reasoning | NIv2 | fs_opt | 9 | train |
Given a premise and two alternatives, choose the alternative that is a more plausible cause or effect of the situation described by the premise. The input format is "premise
(1)alternative_1(2)alternative_2", the output should either be "1" or "2" based on your judgment.
Example Input: The executive decided not to hir... | 1
| task827_copa_commonsense_reasoning | NIv2 | fs_opt | 3 | train |
Given a premise and two alternatives, choose the alternative that is a more plausible cause or effect of the situation described by the premise. The input format is "premise
(1)alternative_1(2)alternative_2", the output should either be "1" or "2" based on your judgment.
--------
Question: A tornado came through the to... | 1
| task827_copa_commonsense_reasoning | NIv2 | fs_opt | 7 | test |
Given a premise and two alternatives, choose the alternative that is a more plausible cause or effect of the situation described by the premise. The input format is "premise
(1)alternative_1(2)alternative_2", the output should either be "1" or "2" based on your judgment.
--------
Question: The artist mixed yellow paint... | 1
| task827_copa_commonsense_reasoning | NIv2 | fs_opt | 7 | validation |
Teacher:In this task, you are given two strings A, B. Find the longest common substring in the strings A and B.
Teacher: Now, understand the problem? Solve this instance: xOqVCqWTHZCXulhl, DgqVCqWTHZCZMmqiziag
Student: | qVCqWTHZC | task600_find_the_longest_common_substring_in_two_strings | NIv2 | zs_opt | 6 | train |
In this task, you are given two strings A, B. Find the longest common substring in the strings A and B.
Q: pJfLBkhOsL, fcBkhOxr
A: | BkhO | task600_find_the_longest_common_substring_in_two_strings | NIv2 | zs_opt | 4 | train |
In this task, you are given two strings A, B. Find the longest common substring in the strings A and B.
Ex Input:
JAGuNgaUudP, eojvKNgaUuQg
Ex Output:
NgaUu
Ex Input:
QqtCFzXHPNFXx, XECFzXHPSGwUuk
Ex Output:
CFzXHP
Ex Input:
NPMzIONy, pAMzIOnJo
Ex Output:
| MzIO
| task600_find_the_longest_common_substring_in_two_strings | NIv2 | fs_opt | 1 | train |
In this task, you are given two strings A, B. Find the longest common substring in the strings A and B.
Q: KEZVzc, hrZVSd
A: | ZV | task600_find_the_longest_common_substring_in_two_strings | NIv2 | zs_opt | 4 | train |
Instructions: In this task, you are given two strings A, B. Find the longest common substring in the strings A and B.
Input: RIxEUWcLmnMMSCGaLX, GwWgtsxEUWcLmnsGFeRJRn
Output: | xEUWcLmn | task600_find_the_longest_common_substring_in_two_strings | NIv2 | zs_opt | 3 | train |
In this task, you are given two strings A, B. Find the longest common substring in the strings A and B.
Q: mXHhaCEIwqwEZcz, JZPXbYHhaCEIwZmna
A: HhaCEIw
****
Q: fdxgzAMP, xrcxgzYW
A: xgz
****
Q: WIMtNNsjzrKYrJObpe, elMtNNsjzrKbG
A: | MtNNsjzrK
****
| task600_find_the_longest_common_substring_in_two_strings | NIv2 | fs_opt | 4 | train |
In this task, you are given two strings A, B. Find the longest common substring in the strings A and B.
sCzctHRVGZCavWYUzvDxipW, gBAiISZGZCavWYUvv | GZCavWYU | task600_find_the_longest_common_substring_in_two_strings | NIv2 | zs_opt | 0 | train |
Detailed Instructions: In this task, you are given two strings A, B. Find the longest common substring in the strings A and B.
Q: PyAjniohBNBbDcm, RtAZxtniohBNUEwNY
A: | niohBN | task600_find_the_longest_common_substring_in_two_strings | NIv2 | zs_opt | 9 | train |
Instructions: In this task, you are given two strings A, B. Find the longest common substring in the strings A and B.
Input: aYBjDIolycgCCkQqwSyMrFR, QleSgDolycgCCkQrSaO
Output: | olycgCCkQ | task600_find_the_longest_common_substring_in_two_strings | NIv2 | zs_opt | 3 | test |
Definition: In this task, you are given two strings A, B. Find the longest common substring in the strings A and B.
Input: BlCNTtegvlQvvzBgSGLTstN, bSdQvvzBgSGLTHERg
Output: | QvvzBgSGLT | task600_find_the_longest_common_substring_in_two_strings | NIv2 | zs_opt | 2 | validation |
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